Riham Mansour

886 citations
5 papers · 15 · h-index 3

Impact in

Papers in

    • Web Data Mining and Analysis 2
    • Text and Document Classification Technologies 2
    • Topic Modeling 2
    • Sentiment Analysis and Opinion Mining 1
    • Natural Language Processing Techniques 1
Journals
Arabian Journal for Science and Engineering (1 paper)Recent Advances in Natural Language Processing (1 paper)International Conference on Computational Linguistics (1 paper)

In The Last Decade

Riham Mansour

5 papers receiving 15 citations

Peers

Riham Mansour
Comparison fields: 5 of 9
  • Geography, Planning and Development 4
  • Transportation 4
  • Artificial Intelligence 9
  • Signal Processing 3
  • Communication 1
Replace L. F. Chaparro Sierra with:
L. F. Chaparro Sierra Colombia
Shubham Jain France
Siu-Ming Yiu Hong Kong
François Garillot United States
Thibault Laugel France
Cem Anil Canada
Jonathan Crabbé United Kingdom
Liam Fowl United States
Artidoro Pagnoni United States
Bonaventure F. P. Dossou Canada
Riham Mansour relative to L. F. Chaparro Sierra Colombia L. F. Chaparro Sierra's profile →
Citations per field
00.5×1.5×
L. F. Chaparro Sierra · 1×
Citations per year

Countries citing papers authored by Riham Mansour

Since Specialization
Citations

This map shows the geographic impact of Riham Mansour's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Riham Mansour with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Riham Mansour more than expected).

Fields of papers citing papers by Riham Mansour

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Riham Mansour. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Riham Mansour. The network helps show where Riham Mansour may publish in the future.

Co-authors

The 5 scholars most cited alongside Riham Mansour, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Riham Mansour Line = papers co-authored together Riham Mansour links everyone, so they are left out of the graph.

All Works

5 of 5 papers shown
#Work
1
Revisiting the Old Kitchen Sink: Do we Need Sentiment Domain Adaptation?
20135
2 20155
3
Augmenting Business Entities with Salient Terms from Twitter
20142
4 20182
5 20191

About Riham Mansour

Riham Mansour is a scholar working on Information Systems, Artificial Intelligence, Communication, Statistical and Nonlinear Physics and Transportation, having authored 5 papers that have together received 15 indexed citations. Recurring topics across this work include Web Data Mining and Analysis (2 papers), Text and Document Classification Technologies (2 papers), Topic Modeling (2 papers), Sentiment Analysis and Opinion Mining (1 paper), Natural Language Processing Techniques (1 paper), Complex Network Analysis Techniques (1 paper), Wikis in Education and Collaboration (1 paper) and Geographic Information Systems Studies (1 paper). The work is most often cited by research in Geography, Planning and Development (4 citations), Transportation (4 citations), Artificial Intelligence (9 citations), Signal Processing (3 citations) and Communication (1 citation). Riham Mansour has collaborated with scholars based in Egypt, United Kingdom and United States. Frequent co-authors include Hicham G. Elmongui, Elsayed E. Hemayed, Vanessa Murdock, Michael Gamon and Saurabh Bagchi. Their work appears in journals such as Arabian Journal for Science and Engineering, Recent Advances in Natural Language Processing and International Conference on Computational Linguistics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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